scholarly article | Q13442814 |
P356 | DOI | 10.1002/MNFR.201601050 |
P698 | PubMed publication ID | 28586169 |
P50 | author | Michael J. Gibney | Q60473937 |
Lorraine Brennan | Q22964830 | ||
P2093 | author name string | Anne P Nugent | |
Janette Walton | |||
Eibhlin Carr | |||
Helena Gibbons | |||
Breige A McNulty | |||
Albert Flynn | |||
P2860 | cites work | Dietary patterns derived from principal component- and k-means cluster analysis: long-term association with coronary heart disease and stroke | Q44612541 |
Application of a new statistical method to derive dietary patterns in nutritional epidemiology | Q44884897 | ||
Identification of biomarkers for intake of protein from meat, dairy products and grains: a controlled dietary intervention study. | Q45013259 | ||
Dietary patterns in middle-aged Irish men and women defined by cluster analysis. | Q45153343 | ||
N-acetylglutamate and N-acetylaspartate in soybeans (Glycine max L.), maize (Zea mays L.), [corrected] and other foodstuffs. | Q45925365 | ||
Intestinal absorption and blood clearance of L-histidine-related compounds after ingestion of anserine in humans and comparison to anserine-containing diets. | Q46102330 | ||
Dietary intake patterns are reflected in metabolomic profiles: potential role in dietary assessment studies | Q46576542 | ||
Effects of orange juice and proline betaine on glycine betaine and homocysteine in healthy male subjects. | Q46865282 | ||
Vitamin D status of Irish adults: findings from the National Adult Nutrition Survey | Q47277870 | ||
Variation of serum metabolites related to habitual diet: a targeted metabolomic approach in EPIC-Potsdam. | Q50487358 | ||
Dietary patterns, meat intake, and the risk of type 2 diabetes in women. | Q50781994 | ||
Use of metabotyping for the delivery of personalised nutrition. | Q51034019 | ||
Orthogonal projections to latent structures (O-PLS) | Q56435041 | ||
Dietary patterns and gastric cancer risk: a systematic review and meta-analysis | Q26851692 | ||
Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. DASH-Sodium Collaborative Research Group | Q28141498 | ||
Dietary patterns and breast cancer risk: a systematic review and meta-analysis | Q28275629 | ||
Can we use biomarkers in combination with self-reports to strengthen the analysis of nutritional epidemiologic studies? | Q33738935 | ||
Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption | Q33997617 | ||
Adherence to a Mediterranean diet and survival in a Greek population | Q34208988 | ||
The Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets and colorectal cancer | Q34308110 | ||
Beneficial effects of a Dietary Approaches to Stop Hypertension eating plan on features of the metabolic syndrome | Q34470001 | ||
Vitamin D deficiency and risk of cardiovascular disease | Q34586829 | ||
The effect of Mediterranean diet on metabolic syndrome and its components: a meta-analysis of 50 studies and 534,906 individuals. | Q34627475 | ||
Mediterranean dietary pattern and cancer risk in the EPIC cohort | Q34628230 | ||
Urinary biomarkers of meat consumption | Q35036624 | ||
Bias in dietary-report instruments and its implications for nutritional epidemiology | Q35084175 | ||
Biomarkers in nutritional epidemiology | Q35085708 | ||
Energy balance measurement: when something is not better than nothing | Q35602887 | ||
The serum metabolite response to diet intervention with probiotic acidified milk in irritable bowel syndrome patients is indistinguishable from that of non-probiotic acidified milk by 1H NMR-based metabonomic analysis | Q35670842 | ||
Assessment of the effect of high or low protein diet on the human urine metabolome as measured by NMR. | Q35813280 | ||
Assessment of dietary exposure related to dietary GI and fibre intake in a nutritional metabolomic study of human urine | Q35863388 | ||
The Mediterranean-style dietary pattern and mortality among men and women with cardiovascular disease | Q37390648 | ||
Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics | Q39811810 | ||
Plasma fatty acid patterns reflect dietary habits and metabolic health: A cross-sectional study | Q39877860 | ||
Dietary patterns: from nutritional epidemiologic analysis to national guidelines | Q42588918 | ||
Identification of biochemical changes in lactovegetarian urine using 1H NMR spectroscopy and pattern recognition | Q43217844 | ||
Simultaneous determination of artificial sweeteners, preservatives, caffeine, theobromine and theophylline in food and pharmaceutical preparations by ion chromatography | Q43838715 | ||
Simultaneous determination of caffeine, theobromine, and theophylline by high-performance liquid chromatography | Q43900656 | ||
Comparative analysis of a-priori and a-posteriori dietary patterns using state-of-the-art classification algorithms: a case/case-control study. | Q44172638 | ||
Hippuric acid in 24-hour urine collections is a potential biomarker for fruit and vegetable consumption in healthy children and adolescents | Q44246490 | ||
Untargeted metabolomics as a screening tool for estimating compliance to a dietary pattern | Q44587299 | ||
P577 | publication date | 2017-06-06 | |
P1433 | published in | Molecular Nutrition and Food Research | Q15751861 |
P1476 | title | Metabolomic-based identification of clusters that reflect dietary patterns |
Q92191147 | Impact of a High Protein Intake on the Plasma Metabolome in Elderly Males: 10 Week Randomized Dietary Intervention |
Q90632901 | Metabolic Trajectories Following Contrasting Prudent and Western Diets from Food Provisions: Identifying Robust Biomarkers of Short-Term Changes in Habitual Diet |
Q91535772 | Metabolomic Based Approach to Identify Biomarkers of Apple Intake |
Q61812628 | Metabolomics and Microbiomes as Potential Tools to Evaluate the Effects of the Mediterranean Diet |
Q91271571 | Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies |
Q95838685 | Potential of food intake biomarkers in nutrition research |
Search more.